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tool monkey

Recently I have been applying Kendall’s Tau as an evaluation metric to assess how well a regression model ranks input samples, with respect to …

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Recently I have been applying Kendall’s Tau as an evaluation metric to assess how well a regression model ranks input samples, with respect to …
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tool monkey | erikerlandson.github.io Reviews

https://erikerlandson.github.io

Recently I have been applying Kendall’s Tau as an evaluation metric to assess how well a regression model ranks input samples, with respect to …

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Parallel K-Medoids Using Scala ParSeq - tool monkey

http://erikerlandson.github.io/blog/2015/05/06/parallel-k-medoids-using-scala-parseq

Adventures of an unfrozen caveman programmer. Parallel K-Medoids Using Scala ParSeq. Scala supplies a parallel collections library. That was designed to make it easy for a programmer to add parallel computing over the elements in a collection. In this post, I will describe a case study of applying Scala’s parallel collections to cleanly implement multithreading support for training a K-Medoids clustering model. But no notion of summation that could be used to compute a geometric centroid. With this in mi...

2

Faster Random Samples With Gap Sampling - tool monkey

http://erikerlandson.github.io/blog/2014/09/11/faster-random-samples-with-gap-sampling

Adventures of an unfrozen caveman programmer. Faster Random Samples With Gap Sampling. Update (April 4, 2016): my colleague RJ Nowling. Ran across a paper by J.S. Vitter. That shows Vitter developed the trick of accelerating sampling with a sampling-gap distribution in 1987 – I re-invented Vitter’s wheel 30 years after the fact! I’m surprised it never caught on, as it is not much harder to implement than the naive version. It is random access. Its size is known. It can be destructively modified. Sample(d...

3

Generalizing Kendall's Tau - tool monkey

http://erikerlandson.github.io/blog/2015/08/14/generalizing-kendalls-tau

Adventures of an unfrozen caveman programmer. Recently I have been applying Kendall’s Tau. As an evaluation metric to assess how well a regression model ranks input samples, with respect to a known correct ranking. A Review of Kendall’s Tau. I’ll start with a brief review of Kendall’s Tau. For more depth, a good place to start is the Wikipedia article at the link above. 8220;concordant” pairs) and the number of such pairs whose ordering. The commonly-used formulation of Kendall’s Tau is the “...The formu...

4

Deferring Spark Actions to Lazy Transforms With the Promise RDD - tool monkey

http://erikerlandson.github.io/blog/2014/07/29/deferring-spark-actions-to-lazy-transforms-with-the-promise-rdd

Adventures of an unfrozen caveman programmer. Deferring Spark Actions to Lazy Transforms With the Promise RDD. In a previous post. I described a method for implementing the Scala. Transform for Spark RDDs. That implementation came at a cost of subverting the RDD lazy transform model; it forced the computation of one or more input RDD partitions at call time instead of deferring partition computation, and so behaved more like a Spark action than a transform. The Promise RDD (aka. To a true lazy transform&...

5

Monadic 'break' and 'continue' for Scala Sequence Comprehensions - tool monkey

http://erikerlandson.github.io/blog/2015/01/24/monadic-break-and-continue-for-scala-sequence-comprehensions

Adventures of an unfrozen caveman programmer. Monadic 'break' and 'continue' for Scala Sequence Comprehensions. Author’s note: I’ve since received some excellent feedback from the Scala community, which I included in some end notes. Author’s note the 2nd: I later realized I could apply an implicit conversion and mediator class to preserve the traditional ordering: the code has been updated with that approach. Author’s note the 3rd: This concept has been submitted to the Scala project as JIRA SI-9120.

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Effective continuous integration for Spark projects - Chapeau

http://chapeau.freevariable.com/2015/04/spark-apps-and-ci.html

Effective continuous integration for Spark projects. Is a small library of helper code intended to make it easier to build real-world Spark applications;. Most of it is factored out from applications we’ve developed internally at Red Hat. We have a couple of long-term goals for the Silex project:. We want to make it very easy for us to spin up on new data-processing problems without spending a lot of time dealing with accidental complexity, and. When running tests locally, creating a Spark context with.

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Chapeau

http://chapeau.freevariable.com/posts/2

Notes from Flink Forward. I was in Berlin last week for Flink Forward. The inaugural Apache Flink conference. I’m still learning about Flink, and Flink Forward was a great place to learn more. In this post, I’ll share some of what I consider its coolest features and highlight some of the talks I especially enjoyed. Videos of the talks should all be online soon, so you’ll be able to check them out as well. Keynotes and lightning talks. Kostas Tzoumas and Stephan Ewan (both of data Artisans) shared a keyno...

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Generalizing Kendall’s Tau. Recently I have been applying Kendall’s Tau. As an evaluation metric to assess how well a regression model ranks input samples, with respect to a known correct ranking. A Review of Kendall’s Tau. I’ll start with a brief review of Kendall’s Tau. For more depth, a good place to start is the Wikipedia article at the link above. 8220;concordant” pairs) and the number of such pairs whose ordering. The commonly-used formulation of Kendall’s Tau is the “Tau-B” stati...The formulation...

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